Visible to the public Improving Power amp; Latency Metrics for Hardware Trojan Detection During High Level Synthesis

TitleImproving Power amp; Latency Metrics for Hardware Trojan Detection During High Level Synthesis
Publication TypeConference Paper
Year of Publication2018
AuthorsShathanaa, R., Ramasubramanian, N.
Conference Name2018 9th International Conference on Computing, Communication and Networking Technologies (ICCCNT)
Date Publishedjul
Keywordsadders, Benchmark testing, cuckoo search algorithm, datapath resource allocation, Design Space Exploration, design space exploration process, design-for-trust techniques, Hardware, hardware trojan, hardware Trojan detection, high level synthesis, integrated chip design, integrated circuit design, integrated circuits, invasive software, latency metrics, Mathematical model, microprocessor chips, power consumption, power metrics, pubcrawl, resilience, Resiliency, resource allocation, Scalability, secure IC design process, semiconductor industry, Space exploration, third party IP cores, Trojan horses, Unroll Factor, work factor metrics
AbstractThe globalization and outsourcing of the semiconductor industry has raised serious concerns about the trustworthiness of the hardware. Importing Third Party IP cores in the Integrated Chip design has opened gates for new form of attacks on hardware. Hardware Trojans embedded in Third Party IPs has necessitated the need for secure IC design process. Design-for-Trust techniques aimed at detection of Hardware Trojans come with overhead in terms of area, latency and power consumption. In this work, we present a Cuckoo Search algorithm based Design Space Exploration process for finding low cost hardware solutions during High Level Synthesis. The exploration is conducted with respect to datapath resource allocation for single and nested loops. The proposed algorithm is compared with existing Hardware Trojan detection mechanisms and experimental results show that the proposed algorithm is able to achieve 3x improvement in Cost when compared existing algorithms.
DOI10.1109/ICCCNT.2018.8494102
Citation Keyshathanaa_improving_2018